Convex Formulation and Efficiency Enhancement for Powered Landing Guidance With Second-Order Cone Probability Constraints

Real-time trajectory optimization is crucial for achieving autonomous guidance in powered landing. However, the existing algorithms often struggle with uncertainties and are unable to handle second-order cone probability constraints, such as control magnitude and direction constraints. In addition,...

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Vydáno v:IEEE transactions on aerospace and electronic systems Ročník 61; číslo 2; s. 1742 - 1763
Hlavní autoři: Li, Wenbo, Gong, Shengping
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.04.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9251, 1557-9603
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Shrnutí:Real-time trajectory optimization is crucial for achieving autonomous guidance in powered landing. However, the existing algorithms often struggle with uncertainties and are unable to handle second-order cone probability constraints, such as control magnitude and direction constraints. In addition, the large-scale and complex nature of these optimization problems hampers real-time performance. This study addresses these shortcomings by presenting a convex formulation suitable for general second-order cone probability constraints and proposing two strategies, conservative approximation and variable reduction, to improve real-time performance. Specifically, the conservative approximation converts spectral norm constraints into second-order cone constraints, while the variable reduction reduces the number of optimization variables. Applied to a powered landing simulation scenario, the proposed approaches effectively handle second-order cone probability constraints and improve real-time performance by two to three orders of magnitude.
Bibliografie:ObjectType-Article-1
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content type line 14
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2024.3458940